Systems Architecture for Quantum Random Access Memory | IEEE Conference Publication | IEEE Xplore

Systems Architecture for Quantum Random Access Memory


Abstract:

Operating on the principles of quantum mechanics, quantum algorithms hold the promise for solving problems that are beyond the reach of the best-available classical algor...Show More

Abstract:

Operating on the principles of quantum mechanics, quantum algorithms hold the promise for solving problems that are beyond the reach of the best-available classical algorithms. An integral part of realizing such speedup is the implementation of quantum queries, which read data into forms that quantum computers can process. Quantum random access memory (QRAM) is a promising architecture for realizing quantum queries. However, implementing QRAM in practice poses significant challenges, including query latency, memory capacity and fault-tolerance.In this paper, we propose the first end-to-end system architecture for QRAM. First, we introduce a novel QRAM that hybridizes two existing implementations and achieves asymptotically superior scaling in space (qubit number) and time (circuit depth). Like in classical virtual memory, our construction enables queries to a virtual address space larger than what is actually available in hardware. Second, we present a compilation framework to synthesize, map, and schedule QRAM circuits on realistic hardware. For the first time, we demonstrate how to embed large-scale QRAM on a 2D Euclidean space, such as a 2D square grid layout, with minimal routing overhead. Third, we show how to leverage the intrinsic biased-noise resilience of the proposed QRAM for implementation on either Noisy Intermediate-Scale Quantum (NISQ) or Fault-Tolerant Quantum Computing (FTQC) hardware. Finally, we validate these results numerically via both classical simulation and quantum hardware experimentation. Our novel Feynman-path-based simulator allows for efficient simulation of noisy QRAM circuits at a larger scale than previously possible. Collectively, our results outline the set of software and hardware controls needed to implement practical QRAM.CCS CONCEPTS• Computer systems organization → Quantum computing; • Hardware→Quantum technologies.
Date of Conference: 28 October 2023 - 01 November 2023
Date Added to IEEE Xplore: 06 February 2024
Print on Demand(PoD) ISBN:979-8-3503-3056-4
Conference Location: Toronto, ON, Canada

Funding Agency:


1 INTRODUCTION

Quantum computers hold the potential to solve problems that are beyond the reach of conventional digital computers. Such quantum speedup, as understood theoretically, arises from the utilization of quantum mechanical properties such as superposition and entanglement to process information more efficiently and rapidly [45]. Some of the most promising quantum computing applications include quantum searching [26], optimization problems [55], molecular simulation [21], [39], data processing for machine learning [4], [30], and cryptography [52]. For example, the quantum algorithm by Grover [26] for searching an unordered database of size N makes only order of queries to the database. This is a -speedup over the best classical algorithms, which require order of N queries when given access to the same database.

References

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